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International Joint Conference on Neural Networks (IJCNN)

作者： C.S. Marino A. Sarajedini P. Chau Department of Electrical and Computer Engineering University of California La Jolla CA USA

Advancements in FPGA technology have permitted near real-time signal processing. To achieve real-time signal processing one can consider reduced complexity algorithms. An important component of many modern signal processing algorithms is calculation of the signal autocorrelation matrix. Instead of calculating the conventional autocorrelation, we propose to use the complex hybrid-sign and the quadruplex algorithms introduced by Jacovitti (1987) and Sullivan et al. (1995), respectively. The accuracy of these algorithms is of concern especially in applications which are resolution sensitive. In particular, we consider the effect of the hybrid and quadruplex approximations on the direction of arrival (DOA) estimate produced by beamforming. We show that the variance of the DOA estimate approaches the theoretical estimate predicted by Sullivan for low S/N ratio. At high S/N ratio, the bias and variance of the quadruplex estimate are actually better than the conventional method.

关键词： Digital signal processing Array signal processing Direction of arrival estimation signal processing algorithms Antenna arrays Adaptive signal processing signal processing Autocorrelation Estimation theory Linear antenna arrays

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Chirp Sub-pulse Stepped Frequency Radar signal processing

Chirp Sub-pulse Stepped Frequency Radar Signal Processing

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International Symposiums on Information processing (ISIP)

作者： Wei Chongyu Yang Yang Cheng Junxian Qingdao University of Science and Technology Qingdao China Qingdao RPM Electronics Company Limited Qingdao China

Chirp-SF signal is a new kind of high range of resolution signal. This paper firstly points out that the traditional signal processing methods will cause “ghost images” when there is more than one scatter in a distance unit. Then a new method which including interfacing each sub-pulse in the Timeline and frequency shifting to Constitute a FM signal is proposed. We can solve this problem and have a high range resolution by execute the pulse compression on the synthetic signal. In the end, the simulation result is shown to prove the correction of the Algorithm.

关键词： Chirp signal resolution Frequency domain analysis Radar Time domain analysis signal processing algorithms

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Noise reduction and PD measurements using digital filter and signal processing technique in HV substations

Noise reduction and PD measurements using digital filter and...

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International Symposium on Electrical Insulating Materials

作者： M. Kozako Z. Tian H. Okubo N. Shibata M. Hikita Department of Electrical Engineering Kyushu Institute of Technology Kitakyushu Japan Department of Electrical Engineering University of Nagoya Nagoya Japan Kyushu Electric Power Corporation Kitakyushu Japan

It is our aim to establish a proper noise reduction algorithm for partial discharge (PD) detection and measurements of electric power apparatus by using digital signal processing techniques. Examinations of noise diminution by an adaptive predictor filter technique have been done in both the laboratory and on-site practical environments on the basis of measurements of PD signals in SF/sub 6/ gas and the real noises as well as interferences. We measured the electromagnetic noises in practical HV and EHV substations and utilized the noise reduction method. As a result, sinusoidal continuous noises were considerably reduced without a priori knowledge of PD signals and noise characteristics, so that the technique is promising to be used for future applications in actual power substations.

关键词： Noise reduction Noise measurement Digital filters Partial discharges Working environment noise Partial discharge measurement Electromagnetic measurements Substations signal processing algorithms Power measurement

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Using signal processing techniques for DNA sequence comparison

Using signal processing techniques for DNA sequence comparis...

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Annual Northeast Bioengineering Conference

作者： E.A. Cheever D.B. Searls W. Karunaratne G.C. Overton Department of Engineering Swarthmore College Swarthmore PA USA Paoli Research Center Unisys Corporation Paoli PA USA

The most widely used algorithm for the comparison of two sequences of DNA are O(m*n) on the lengths, m and n, of the sequences been compared. The authors present a comparison algorithm that is O(nlog n) on the length, n, of the longer sequence. This algorithm uses techniques developed for rapid comparison of two discrete signals, in particular, cross-correlation using the fast Fourier transform (FFT). The authors treat the DNA as a discrete signal with each nucleotide base represented by a single point in the signal. There are only four possible values that the signal can assume which they represent by one of four complex numbers. The comparison is made by performing a cross correlation between one signal and the complex conjugate of the other. Any significant peak in the resulting signal indicates a strong similarity between the two sequences. The authors present the results of comparison of two strains of the human immunodeficiency virus and of human and simian immunodeficiency viruses. Their results suggest that this technique is a powerful method for comparing very long sequences of DNA.< >

关键词： signal processing DNA Sequences signal processing algorithms Humans Genomics Bioinformatics Fourier transforms Fast Fourier transforms Educational institutions

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Lattice filter with adjustable gains and its application in optical signal processing

Lattice filter with adjustable gains and its application in ...

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IEEE/SP Workshop on Statistical signal processing (SSP)

作者： I.M.S. Panahi G. Kannan L.R. Hunt D.L. MacFarlane J. Tong Department of Electrical Engineering University of Texas Dallas TX USA

In this paper, we consider a class of N-th order lattice filter with gains as an extension to the traditional lattice filter structures and develop analysis and synthesis of such filters. In the analysis-synthesis parts, we present recursive methods to derive the input-output transfer function of the filter in terms of parameters of the lattice structure such as the time delay, gains, transmission and reflection coefficients and vice versa. Stability of the filter is analyzed and an algorithm to test the stability is proposed. This class of MIMO lattice filters with adjustable gains models integrated photonic devices under development in our labs for optical communication and high speed signal processing applications. Our signal processing approach to characterizing this type of lattice structures can also be used in filter realization by VLSI, FPGA, or programmable processors for acoustic or speech applications

关键词： Lattices Optical filters Optical signal processing signal processing algorithms Stability analysis Acoustic signal processing signal synthesis Transfer functions Delay effects Optical reflection

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signal processing and complexity of computation

Signal processing and complexity of computation

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International Conference on Acoustics, Speech, and signal processing (ICASSP)

作者： S. Winograd International Business Machines Corporation IBM Thomas J. Watson Research Center Yorktown Heights NY USA

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Minimum initiation interval of multi-module recurrent signal processing algorithm realization with fixed communication delay

Minimum initiation interval of multi-module recurrent signal...

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International Conference on Acoustics, Speech, and signal processing (ICASSP)

作者： H.-Y. Tyan Y.H. Hu Electrical Engineering Department Ohio State Uinversity Columbus OH USA Department of Electrical and Computer Engineering University of Wisconsin Madison WI USA

A novel iterative algorithm is proposed to compute the theoretical minimum initiation interval of a given recurrent algorithm when there is a known, fixed inter-module communication delay. Specifically, for a twin-module implementation problem, a novel representation called necessary initiation interval is introduced to facilitate the development of an iterative algorithm which yields both the minimum initiation interval and the corresponding cut set of the cyclic iterative computational dependence graph (ICDG). The convergence of this iterative algorithm in finite iterations is also proved.

关键词： signal processing algorithms Delay Iterative algorithms IIR filters Digital filters Upper bound Throughput Digital signal processing chips Integrated circuit packaging Digital signal processing

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Direct-Optimization-Based DC Dictionary Learning With the MCP Regularizer

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IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2023年第7期34卷 3568-3579页

作者： Li, Zhenni Yang, Zuyuan Zhao, Haoli Xie, Shengli Guangdong Univ Technol Sch Automat Guangzhou 510006 Peoples R China Guangdong HongKong Macao Joint Lab Smart Discrete Guangzhou 510006 Peoples R China Guangdong Key Lab IoT Informat Technol GDUT Guangzhou 510006 Peoples R China Sun Yat Sen Univ Sch Data & Comp Sci Guangzhou 510006 Peoples R China Minist Educ Key Lab Intelligent Informat Proc & Syst Integrat Guangzhou 510006 Peoples R China

Direct-optimization-based dictionary learning has attracted increasing attention for improving computational efficiency. However, the existing direct optimization scheme can only be applied to limited dictionary learning problems, and it remains an open problem to prove that the whole sequence obtained by the algorithm converges to a critical point of the objective function. In this article, we propose a novel direct-optimization-based dictionary learning algorithm using the minimax concave penalty (MCP) as a sparsity regularizer that can enforce strong sparsity and obtain accurate estimation. For solving the corresponding optimization problem, we first decompose the nonconvex MCP into two convex components. Then, we employ the difference of the convex functions algorithm and the nonconvex proximal-splitting algorithm to process the resulting subproblems. Thus, the direct optimization approach can be extended to a broader class of dictionary learning problems, even if the sparsity regularizer is nonconvex. In addition, the convergence guarantee for the proposed algorithm can be theoretically proven. Our numerical simulations demonstrate that the proposed algorithm has good convergence performances in different cases and robust dictionary-recovery capabilities. When applied to sparse approximations, the proposed approach can obtain sparser and less error estimation than the different sparsity regularizers in existing methods. In addition, the proposed algorithm has robustness in image denoising and key-frame extraction.

关键词： Machine learning Optimization Dictionaries Convergence Convex functions signal processing algorithms Approximation algorithms Convergence analysis dictionary learning direct optimization minimax concave penalty (MCP) regularizer

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Robust Iterative Sparse ML-Based Approaches for CES Data Model: Application to DOA Estimation

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IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS 2024年第6期60卷 8635-8650页

作者： Abeida, Habti Glentis, George-Othon Alsharef, Mohammad Li, Jian Taif Univ Coll Engn Dept Elect Engn Taif 21944 Saudi Arabia Univ Peloponnese Dept Informat & Telecommun Tripolis 22100 Greece Univ Florida Dept Elect & Comp Engn Gainesville FL 32611 USA

SCM is widely used in the design of array signal processing algorithms that perform well for CCG distributed samples. However, SCM-based DOA estimation algorithms are inaccurate for CES data models. This article aims to extend the conventional SCM-based iterative sparse SMLA for DOA estimation to encompass more general circular CES distributed observations. These extended RSMLA use robust CES-based ML-estimators of the CM instead of SCM, or more generally M-estimators. Joint and interleaved computation of M-estimators and the RSMLA are also proposed [denoted as IRSMLA algorithms] when the size of the observed CES vector, M, is of the same order as the samples size, N, or when N < M. To improve DOA estimation accuracy and eliminate grid mismatch, refined approaches (referred to as RSMLA-RML) that combines the power-based RSMLA and robust ML (RML) methods are also proposed, in which an alternative RML cost function is minimized over a scalar DOA parameter. Performance comparisons are made between the developed approaches and existing DOA estimation algorithms as well as CRB in terms of sample size, SNR, DOA separation, signal source correlation parameters, and computational cost, demonstrating superior performance over existing schemes for heavy-tailed CES distributed observations. Moreover, it is experimentally demonstrated that the proposed algorithms perform effectively even when the encountered source signals are coherent, despite being derived under the assumption of uncorrelated sources.

关键词： Direction-of-arrival estimation signal processing algorithms Accuracy Maximum likelihood estimation signal to noise ratio Multiple signal classification Vectors Circular complex elliptically symmetric (CES) distributions direction of arrival (DOA) estimation M-estimators stochastic maximum likelihood approaches (SMLA) algorithms sparse representation

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Accelerating Two-Phase Multiobjective Evolutionary Algorithm for Electric Location-Routing Problems

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IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 2023年第9期24卷 9121-9136页

作者： Wang, Chao Liu, Rongrong Su, Yansen Zhang, Xingyi Anhui Univ Minist Educ Sch Artificial Intelligence Informat Mat & Intelligent Sensing Lab Anhui Prov Hefei Peoples R China Anhui Univ Engn Res Ctr Autonomous Unmanned Syst Technol Sch Artificial Intelligence Minist Educ Hefei 230601 Peoples R China Anhui Univ Minist Educ Key Lab Intelligent Comp & Signal Proc Hefei 230601 Peoples R China Anhui Univ Sch Artificial Intelligence Hefei 230601 Peoples R China

Electric location-routing problem is a challenging problem consisting of the optimization of electric vehicle routing and charging facility location, simultaneously. Existing algorithms generally adopt the two-phase search strategy to alternately optimize the routing and the location. However, they are usually criticized for the inefficiency as the problem scale increases. In order to improve the search efficiency in each phase, we propose an accelerating two-phase multiobjective evolutionary algorithm, where the learning method is used to mine the useful information from the historical search process to generate the high-quality routing and location offspring. To be specific, in the routing optimization phase, an interpolation method is developed to extract the frequent visiting orders existing in the historical best solutions. These frequent visiting orders are used to create potential routing offspring that can accelerate the convergence toward the optimal solutions. In the location optimization phase, a surrogate model is used to approximatively represent the relationship from routing to location, which can directly output a promising location scheme for a given routing offspring and thus reduce the optimization time. Experimental results on different scales of test instances demonstrate the competitiveness of the proposed algorithm in comparison with several state of-the-art algorithms, including four widely used heuristic algorithms and two multiobjective evolutionary algorithms.

关键词： Routing Search problems Optimization Heuristic algorithms Evolutionary computation Batteries signal processing algorithms Electric location-routing problem multiobjective optimization evolutionary algorithm interpolation surrogate

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